Recursive Bayesian search-and-tracking using coordinated UAVs for lost targets

被引:128
作者
Furukawa, Tomonari [1 ]
Bourgault, Frederic [2 ]
Lavis, Benjamin [1 ]
Durrant-Whyte, Hugh F. [2 ]
机构
[1] Univ New S Wales, ARC, Ctr Excellence Autonomous Syst, Sch Mech & Mfg Engn, Sydney, NSW 2052, Australia
[2] Univ Sydney, Australian Ctr Field Robot, Sydney, NSW 2006, Australia
来源
2006 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-10 | 2006年
基金
澳大利亚研究理事会;
关键词
D O I
10.1109/ROBOT.2006.1642081
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a coordinated control technique that allows heterogeneous vehicles to autonomously search for and track multiple targets using recursive Bayesian filtering. A unified sensor model and a unified objective function are proposed to enable search-and-tracking (SAT) within the recursive Bayesian filter framework. The strength of the proposed technique is that a vehicle can switch its task mode between search and tracking while maintaining and using information collected during the operation. Numerical results first show the effectiveness of the proposed technique when a found target becomes lost and must be searched for again. The proposed technique was then applied to a practical marine search-andrescue (SAR) scenario where heterogeneous vehicles coordinated to search for and track multiple targets. The result demonstrates the applicability of the technique to real search world scenarios.
引用
收藏
页码:2521 / +
页数:2
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